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M. Frank Norman

Researcher at University of Pennsylvania

Publications -  29
Citations -  1932

M. Frank Norman is an academic researcher from University of Pennsylvania. The author has contributed to research in topics: Genetic model & Markov process. The author has an hindex of 17, co-authored 29 publications receiving 1837 citations. Previous affiliations of M. Frank Norman include Stanford University & Dartmouth College.

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Neurocognitive Correlates of Socioeconomic Status in Kindergarten Children.

TL;DR: Relations among language, executive function, SES and specific aspects of early childhood experience were explored, revealing intercorrelations and a seemingly predominant role of individual differences in language ability involved in SES associations with executive function.
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Development and Validation of a Telephone Questionnaire to Characterize Lymphedema in Women Treated for Breast Cancer

TL;DR: A few straightforward questions exhibited excellent agreement with physical therapists' assessments for identifying at least moderate lymphedema, and the sensitivity of the questionnaire varied from 0.86 to 0.92 and specificity was 0.90; however, sensitivity was higher than specificity for the diagnosis of any lyMPhedema.
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SATs, Achievement Tests, and High-School Class Rank as Predictors of College Performance.

TL;DR: This article used regression coefficients to predict student's grades at the University of Pennsylvania from linear combinations of high school class rank (CLR), total scholastic-aptitude-test score (SAT), and average achievement test score (ACH), all of which are available in applications for admission to selective institutions.
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Some convergence theorems for stochastic learning models with distance diminishing operators

TL;DR: In this paper, a broad mathematical framework is considered that includes stochastic learning models with distance diminishing operators for experiments with finite numbers of responses and simple contingent reinforcement, and convergence theorems are presented that subsume most previous results about such models, and extend them in a variety of ways.